131 related articles for article (PubMed ID: 38368358)
1. The effectiveness of simple heuristic features in sensor orientation and placement problems in human activity recognition using a single smartphone accelerometer.
Barua A; Jiang X; Fuller D
Biomed Eng Online; 2024 Feb; 23(1):21. PubMed ID: 38368358
[TBL] [Abstract][Full Text] [Related]
2. Exploring Orientation Invariant Heuristic Features with Variant Window Length of 1D-CNN-LSTM in Human Activity Recognition.
Barua A; Fuller D; Musa S; Jiang X
Biosensors (Basel); 2022 Jul; 12(7):. PubMed ID: 35884354
[TBL] [Abstract][Full Text] [Related]
3. Analyzing the Effectiveness and Contribution of Each Axis of Tri-Axial Accelerometer Sensor for Accurate Activity Recognition.
Javed AR; Sarwar MU; Khan S; Iwendi C; Mittal M; Kumar N
Sensors (Basel); 2020 Apr; 20(8):. PubMed ID: 32295298
[TBL] [Abstract][Full Text] [Related]
4. Deep Learning for Activity Recognition in Older People Using a Pocket-Worn Smartphone.
Nan Y; Lovell NH; Redmond SJ; Wang K; Delbaere K; van Schooten KS
Sensors (Basel); 2020 Dec; 20(24):. PubMed ID: 33334028
[TBL] [Abstract][Full Text] [Related]
5. A hybrid deep approach to recognizing student activity and monitoring health physique based on accelerometer data from smartphones.
Xiao L; Luo K; Liu J; Foroughi A
Sci Rep; 2024 Jun; 14(1):14006. PubMed ID: 38890409
[TBL] [Abstract][Full Text] [Related]
6. LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes.
Mekruksavanich S; Jitpattanakul A
Sensors (Basel); 2021 Feb; 21(5):. PubMed ID: 33652697
[TBL] [Abstract][Full Text] [Related]
7. Smartphone-Based Activity Recognition Using Multistream Movelets Combining Accelerometer and Gyroscope Data.
Huang EJ; Yan K; Onnela JP
Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408232
[TBL] [Abstract][Full Text] [Related]
8. Coarse-Fine Convolutional Deep-Learning Strategy for Human Activity Recognition.
Avilés-Cruz C; Ferreyra-Ramírez A; Zúñiga-López A; Villegas-Cortéz J
Sensors (Basel); 2019 Mar; 19(7):. PubMed ID: 30935117
[TBL] [Abstract][Full Text] [Related]
9. Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study.
Davoudi A; Wanigatunga AA; Kheirkhahan M; Corbett DB; Mendoza T; Battula M; Ranka S; Fillingim RB; Manini TM; Rashidi P
JMIR Mhealth Uhealth; 2019 Feb; 7(2):e11270. PubMed ID: 30724739
[TBL] [Abstract][Full Text] [Related]
10. Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors.
Shoaib M; Bosch S; Incel OD; Scholten H; Havinga PJ
Sensors (Basel); 2016 Mar; 16(4):426. PubMed ID: 27023543
[TBL] [Abstract][Full Text] [Related]
11. Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand.
Ebner M; Fetzer T; Bullmann M; Deinzer F; Grzegorzek M
Sensors (Basel); 2020 Nov; 20(22):. PubMed ID: 33212894
[TBL] [Abstract][Full Text] [Related]
12. Human Physical Activity Recognition Using Smartphone Sensors.
Voicu RA; Dobre C; Bajenaru L; Ciobanu RI
Sensors (Basel); 2019 Jan; 19(3):. PubMed ID: 30678039
[TBL] [Abstract][Full Text] [Related]
13. Smartphone Motion Sensor-Based Complex Human Activity Identification Using Deep Stacked Autoencoder Algorithm for Enhanced Smart Healthcare System.
Alo UR; Nweke HF; Teh YW; Murtaza G
Sensors (Basel); 2020 Nov; 20(21):. PubMed ID: 33167424
[TBL] [Abstract][Full Text] [Related]
14. A feasibility study on smartphone accelerometer-based recognition of household activities and influence of smartphone position.
Della Mea V; Quattrin O; Parpinel M
Inform Health Soc Care; 2017 Dec; 42(4):321-334. PubMed ID: 28005434
[TBL] [Abstract][Full Text] [Related]
15. Ensem-HAR: An Ensemble Deep Learning Model for Smartphone Sensor-Based Human Activity Recognition for Measurement of Elderly Health Monitoring.
Bhattacharya D; Sharma D; Kim W; Ijaz MF; Singh PK
Biosensors (Basel); 2022 Jun; 12(6):. PubMed ID: 35735541
[TBL] [Abstract][Full Text] [Related]
16. A Public Domain Dataset for Real-Life Human Activity Recognition Using Smartphone Sensors.
Garcia-Gonzalez D; Rivero D; Fernandez-Blanco E; Luaces MR
Sensors (Basel); 2020 Apr; 20(8):. PubMed ID: 32295028
[TBL] [Abstract][Full Text] [Related]
17. The Effect of Sensor Placement and Number on Physical Activity Recognition and Energy Expenditure Estimation in Older Adults: Validation Study.
Davoudi A; Mardini MT; Nelson D; Albinali F; Ranka S; Rashidi P; Manini TM
JMIR Mhealth Uhealth; 2021 May; 9(5):e23681. PubMed ID: 33938809
[TBL] [Abstract][Full Text] [Related]
18. Exploration of Human Activity Recognition Using a Single Sensor for Stroke Survivors and Able-Bodied People.
Meng L; Zhang A; Chen C; Wang X; Jiang X; Tao L; Fan J; Wu X; Dai C; Zhang Y; Vanrumste B; Tamura T; Chen W
Sensors (Basel); 2021 Jan; 21(3):. PubMed ID: 33530295
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of a smartphone human activity recognition application with able-bodied and stroke participants.
Capela NA; Lemaire ED; Baddour N; Rudolf M; Goljar N; Burger H
J Neuroeng Rehabil; 2016 Jan; 13():5. PubMed ID: 26792670
[TBL] [Abstract][Full Text] [Related]
20. Predicting lying, sitting and walking at different intensities using smartphone accelerometers at three different wear locations: hands, pant pockets, backpack.
Khataeipour SJ; Anaraki JR; Bozorgi A; Rayner M; A Basset F; Fuller D
BMJ Open Sport Exerc Med; 2022; 8(2):e001242. PubMed ID: 35601137
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
